mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-12-21 13:37:47 +00:00
82 lines
2.7 KiB
Markdown
82 lines
2.7 KiB
Markdown
# whisper.cpp
|
|
|
|
Node.js package for Whisper speech recognition
|
|
|
|
Package: https://www.npmjs.com/package/whisper.cpp
|
|
|
|
## Details
|
|
|
|
The performance is comparable to when running `whisper.cpp` in the browser via WASM.
|
|
|
|
The API is currently very rudimentary:
|
|
|
|
https://github.com/ggerganov/whisper.cpp/blob/npm/bindings/javascript/emscripten.cpp
|
|
|
|
I am hoping that there will be interest in contributions and making it better based on what is needed in practice.
|
|
For sample usage check [tests/test-whisper.js](https://github.com/ggerganov/whisper.cpp/blob/npm/tests/test-whisper.js)
|
|
|
|
## Package building + test
|
|
|
|
```bash
|
|
# load emscripten
|
|
source /path/to/emsdk/emsdk_env.sh
|
|
|
|
# clone repo
|
|
git clone https://github.com/ggerganov/whisper.cpp
|
|
cd whisper.cpp
|
|
|
|
# grab base.en model
|
|
./models/download-ggml-model.sh base.en
|
|
|
|
# prepare PCM sample for testing
|
|
ffmpeg -i samples/jfk.wav -f f32le -acodec pcm_f32le samples/jfk.pcmf32
|
|
|
|
# build
|
|
mkdir build-em && cd build-em
|
|
emcmake cmake .. && make -j
|
|
|
|
# run test
|
|
node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
|
|
|
|
# publish npm package
|
|
make publish-npm
|
|
```
|
|
|
|
## Sample run
|
|
|
|
```java
|
|
$ node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
|
|
|
|
whisper_model_load: loading model from 'whisper.bin'
|
|
whisper_model_load: n_vocab = 51864
|
|
whisper_model_load: n_audio_ctx = 1500
|
|
whisper_model_load: n_audio_state = 512
|
|
whisper_model_load: n_audio_head = 8
|
|
whisper_model_load: n_audio_layer = 6
|
|
whisper_model_load: n_text_ctx = 448
|
|
whisper_model_load: n_text_state = 512
|
|
whisper_model_load: n_text_head = 8
|
|
whisper_model_load: n_text_layer = 6
|
|
whisper_model_load: n_mels = 80
|
|
whisper_model_load: f16 = 1
|
|
whisper_model_load: type = 2
|
|
whisper_model_load: adding 1607 extra tokens
|
|
whisper_model_load: mem_required = 506.00 MB
|
|
whisper_model_load: ggml ctx size = 140.60 MB
|
|
whisper_model_load: memory size = 22.83 MB
|
|
whisper_model_load: model size = 140.54 MB
|
|
|
|
system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 1 | BLAS = 0 |
|
|
|
|
operator(): processing 176000 samples, 11.0 sec, 8 threads, 1 processors, lang = en, task = transcribe ...
|
|
|
|
[00:00:00.000 --> 00:00:11.000] And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.
|
|
|
|
whisper_print_timings: load time = 162.37 ms
|
|
whisper_print_timings: mel time = 183.70 ms
|
|
whisper_print_timings: sample time = 4.27 ms
|
|
whisper_print_timings: encode time = 8582.63 ms / 1430.44 ms per layer
|
|
whisper_print_timings: decode time = 436.16 ms / 72.69 ms per layer
|
|
whisper_print_timings: total time = 9370.90 ms
|
|
```
|